def get_input_gen(config, retina):
inputmethod = config['Retina']['inputmethod']
if inputmethod == 'read':
print('Generating input files')
with Timer('input generation'):
gi.gen_input(config)
return None
else:
print('Using input generating function')
return RetinaInputProcessor(config, retina)
def get_input_gen(config, retina):
'''
Depending on configuration input can either be created
in advance and read from file or
generated during simulation by a generator object.
'''
inputmethod = config['Retina']['inputmethod']
if inputmethod == 'read':
print('Generating input files')
with Timer('input generation'):
gi.gen_input(config)
return None
else:
print('Using input generating function')
return RetinaInputProcessor(config, retina)
def get_input_gen(config):
'''
Depending on configuration input can either be created
in advance and read from file or
generated during simulation by a generator object.
'''
inputmethod = config['Retina']['inputmethod']
if inputmethod == 'read':
print('Generating input files')
with Timer('input generation'):
gi.gen_input(config)
return None
else:
print('Using input generating function')
return RetinaInputGenerator(config)
sys.stdout = Tee(script_output_filename(tmpdir))
#algs = ['fftw', 'sfft2-mit', 'sfft1-mit', 'aafft', 'sfft1-eth', 'sfft2-eth']
algs = ['fftw', 'sfft2-mit', 'sfft1-mit', 'aafft']
#algs = ['sfft2-mit']
for snr in snr_db_vals:
print 'snr = {} db ({:.6e})'.format(snr, db_to_ratio(snr))
print ' generating input data ...'
input_filename = []
for instance in range(1, num_instances + 1):
print ' instance {}'.format(instance)
dataf = data_filename_snr(tmpdir, n, k, snr, instance)
gen_input(n, k, dataf, seed=random.randint(0, 2000000000),
stats_file=data_stats_filename_snr(tmpdir, n, k, snr, instance),
noise_variance=snr_db_to_noise_variance(snr, n, k),
randomize_phase=True)
input_filename.append(dataf)
print ' writing index file ...'
indexf = index_filename_snr(tmpdir, n, k, snr)
write_index_file(indexf, input_filename)
for alg in algs:
resultsf = results_filename_snr(tmpdir, alg, n, k, snr)
print ' algorithm: {}'.format(alg)
r = run_experiment(n, k, indexf, alg, l0_eps, num_trials,
seed=random.randint(0, 2000000000), output_file=resultsf)
rel_l2_l2 = compute_relative_l2_l2_errors(r)
ne = 0
for err in rel_l2_l2:
if err > relative_l2_l2_error_threshold:
ne += 1
sys.stdout = Tee(script_output_filename(tmpdir))
algs = ['fftw', 'sfft2-eth', 'sfft2-mit', 'sfft1-eth', 'sfft1-mit', 'aafft']
#algs = ['sfft3-eth', 'sfft2-eth']
for k in kvals:
print 'k = {}'.format(k)
print ' generating input data ...'
input_filename = []
for instance in range(1, num_instances + 1):
print ' instance {}'.format(instance)
dataf = data_filename(tmpdir, n, k, instance)
gen_input(n,
k,
dataf,
random.randint(0, 2000000000),
stats_file=data_stats_filename(tmpdir, n, k, instance))
input_filename.append(dataf)
print ' writing index file ...'
indexf = index_filename(tmpdir, n, k)
write_index_file(indexf, input_filename)
for alg in algs:
resultsf = results_filename(tmpdir, alg, n, k)
print ' algorithm: {}'.format(alg)
r = run_experiment(n, k, indexf, alg, l0_eps, num_trials, resultsf)
ne = num_l0_errors(r)
if ne > 0:
print ' {} L0-errors occurred.'.format(ne)
for f in input_filename:
os.remove(f)
random.seed(7524019)
plot = False
sys.stdout = Tee(script_output_filename(tmpdir))
# algs = ['fftw', 'sfft2-eth', 'sfft2-mit', 'sfft1-eth', 'sfft1-mit', 'aafft']
algs = ["sfft3-eth"]
for k in kvals:
print "k = {}".format(k)
print " generating input data ..."
input_filename = []
for instance in range(1, num_instances + 1):
print " instance {}".format(instance)
dataf = data_filename(tmpdir, n, k, instance)
gen_input(n, k, dataf, random.randint(0, 2000000000), stats_file=data_stats_filename(tmpdir, n, k, instance))
input_filename.append(dataf)
print " writing index file ..."
indexf = index_filename(tmpdir, n, k)
write_index_file(indexf, input_filename)
for alg in algs:
resultsf = results_filename(tmpdir, alg, n, k)
print " algorithm: {}".format(alg)
r = run_experiment(n, k, indexf, alg, l0_eps, num_trials, resultsf)
ne = num_l0_errors(r)
if ne > 0:
print " {} L0-errors occurred.".format(ne)
for f in input_filename:
os.remove(f)
time_results = {}